code: def map_sklearn_tree_into_bartpy(bartpy_tree, sklearn_tree):
      nodes = [None for x in sklearn_tree.children_left]
      nodes[0] = bartpy_tree.nodes[0]
  
      def search(index: int = 0):
          left_child_index, right_child_index = (
              sklearn_tree.children_left[index],
              sklearn_tree.children_right[index],
          )
  
          if (
              left_child_index == -1
          ):  # Trees are binary splits, so only need to check left tree
              return
  
          searched_node: LeafNode = nodes[index]
  
          split_conditions = (
              map_sklearn_split_into_bartpy_split_conditions(
                  sklearn_tree, index
              )
          )
          decision_node = split_node(searched_node, split_conditions)
  
          left_child: LeafNode = decision_node.left_child
          right_child: LeafNode = decision_node.right_child
          left_child.set_value(
              sklearn_tree.value[left_child_index][0][0]
          )
          right_child.set_value(
              sklearn_tree.value[right_child_index][0][0]
          )
  
          mutation = GrowMutation(searched_node, decision_node)
          mutate(bartpy_tree, mutation)
  
          nodes[index] = decision_node
          nodes[left_child_index] = decision_node.left_child
          nodes[right_child_index] = decision_node.right_child
  
          search(left_child_index)
          search(right_child_index)
  
      search()
  
imports: from typing import Tuple, List
  from operator import gt, le
  import numpy
  from sklearn.ensemble import GradientBoostingRegressor, RandomForestRegressor
  from imodels.tree.figs import FIGSRegressor, Node, FIGSRegressorCV
  from sklearn.exceptions import NotFittedError
  from sklearn.tree import DecisionTreeRegressor
  from ..data import make_bartpy_data
  from ..initializers.initializer import Initializer
  from ..mutation import GrowMutation
  from ..node import split_node, LeafNode
  from ..split import Split
  from ..splitcondition import SplitCondition
  from ..tree import Tree, mutate
label_desc: Use image node_id 7 for calling a global function with example usage: map_sklearn_tree_into_bartpy(bartpy_tree, sklearn_tree) without return types